Fitting of Engel Curve Essay Example

the good as either inferior, a necessity, or luxury. This parameter allows us to predict the goods that a society will prioritize during different stages of development and provides insights into the behavior of different sections of society towards that good.

In the present economic situation, it is essential to comprehend the correlation between food spending and income. This understanding enables us to forecast demand and bridge the gap between supply and demand in a developing economy. The income elasticity of food is especially important for policymakers aiming to achieve inclusive development. By establishing this connection, policymakers can create strategies that align with their objective of enhancing the economy.

The analysis of income elasticity involves empirical examination using both Demand curves and Engel Curves. Engel Curves illustrate the connection between household expenditure on particular goods or services and household income. These curves were named after Ernst Engel, a German statistician (1821-1896), who extensively researched this correlation in an article published almost 150 years ago. The most significant discovery from his article is known as "Engel's law," which states that lower-income families devote a greater proportion of their budget to food.

Engel curves can vary based on demographic variables and other consumer characteristics. Empirical Engel curves can have linear or highly nonlinear shapes depending on the goods being analyzed. They have various applications like equivalence scale calculations, welfare comparisons, and determining demand system properties. This includes assessing agreeability and rank. The Engel Curve can be used to study the relationship between food consumption and income, with different models offering unique advantages.

The analysis in this study involves three models: the Linear

Regression Model, the Working-Lesser Model, and the Working-Leser Model. The Linear Regression Model assumes a linear relationship between two variables and calculates elasticity using the equation Y = A0 + A1X. On the other hand, the Working-Lesser Model uses the equation Wi = A0 + AilnX and is considered as an initial empirical model in consumption analysis. In contrast, the Working-Leser model determines each share of the food item through a linear function that includes log prices and total expenditure on all considered food items.

The presented model uses "i" to represent each food item, "wi" to represent the share of expenditure on food "i" out of all "n" food items, and "x" to represent the total expenditure on all included food items. The ordinary least squares method can be used to estimate this model for each individual food item.
Another model, called the Double Log Model, assumes a linear relationship between the logarithms of both dependent and independent variables. The advantage of this relationship is that the coefficients of the income variable directly indicate income elasticity. The equation for this model is lnY = A0 + A1 lnX.

The coefficient of the independent variable, ?= A1, can be directly obtained from the elasticity. The data used in this project was collected by the National Sample Survey (NSS) during its 63rd round of data collection from July 1st, 2005 to June 30th, 2006. The survey gathered information on various expenditures such as food, clothing, medical expenses, alcohol, etc., and demographic details about each family including religion, caste, occupation, age and gender. To validate the collected survey data, it is divided into two samples.